Russell Sage Foundation: Small Grants in Computational Social Science

Scope: RSFs initiative on Computational Social Science supports innovative social science research that utilizes new data and methods to advance our understanding of the research issues that comprise its core social science programs in Social Inequality, Behavioral Economics, Future of Work, and Race, Ethnicity and Immigration. Limited consideration will be given to research that focuses primarily on methodologies, such as causal inference and innovations in data collection. We are primarily interested in research that explores and improves our understanding of social, psychological, political and economic outcomes. For example, can large-scale administrative data linked with other administrative or survey data provide greater insights on educational policies or practices to improve educational or labor market outcomes? Can machine learning techniques used to analyze large volumes of text in greater depth and detail than previously available help shed greater light on questions around inequality, work or immigration? Can data from social media be linked to more structured data to understand social, economic, or political outcomes? More detailed examples of the types of research topics of interest are highlighted in the Computational Social Science (CSS) RFP and a description of recent grants can be found here.